Temporal Coherent Video Decolorization Using Proximity Optimization

Tao, Yizhang; Shen, Yiyi; Sheng, Bin; Li, Ping; Wu, Enhua

doi:10.1145/2949035.2949046

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…Tao et al [84], [85] defined decolorization proximity to measure the similarity of adjacent frames and presented a temporal-coherent video decolorization method using proximity optimization. They then respectively treat frames with low, medium, and high proximities in order to better preserve the quality of these three types of frames.…”

Section: Video Decolorizationmentioning

confidence: 99%

Two Decades of Colorization and Decolorization for Images and Videos

Liu¹

2022

Preprint

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Colorization is a computer-aided process, which aims to give color to a gray image or video. It can be used to enhance black-and-white images, including black-and-white photos, old-fashioned films, and scientific imaging results. On the contrary, decolorization is to convert a color image or video into a grayscale one. A grayscale image or video refers to an image or video with only brightness information without color information. It is the basis of some downstream image processing applications such as pattern recognition, image segmentation, and image enhancement. Different from image decolorization, video decolorization should not only consider the image contrast preservation in each video frame, but also respect the temporal and spatial consistency between video frames. Researchers were devoted to develop decolorization methods by balancing spatial-temporal consistency and algorithm efficiency. With the prevalance of the digital cameras and mobile phones, image and video colorization and decolorization have been paid more and more attention by researchers. This paper gives an overview of the progress of image and video colorization and decolorization methods in the last two decades.

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Section: Video Decolorizationmentioning

confidence: 99%

Two Decades of Colorization and Decolorization for Images and Videos

Liu¹

2022

Preprint

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Decolorization

Liu

2023

Synthesis Lectures on Visual Computing: Computer Graphics, Animation, Computational Photography and Imaging

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Video Decolorization Using Visual Proximity Coherence Optimization

Tao

Shen

Sheng

et al. 2018

IEEE Trans. Cybern.

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Video decolorization is to filter out the color information while preserving the perceivable content in the video as much and correct as possible. Existing methods mainly apply image decolorization strategies on videos, which may be slow and produce incoherent results. In this paper, we propose a video decolorization framework that considers frame coherence and saves decolorization time by referring to the decolorized frames. It has three main contributions. First, we define decolorization proximity to measure the similarity of adjacent frames. Second, we propose three decolorization strategies for frames with low, medium, and high proximities, to preserve the quality of these three types of frames. Third, we propose a novel decolorization Gaussian mixture model to classify the frames and assign appropriate decolorization strategies to them based on their decolorization proximity. To evaluate our results, we measure them from three aspects: 1) qualitative; 2) quantitative; and 3) user study. We apply color contrast preserving ratio and C2G-SSIM to evaluate the quality of single frame decolorization. We propose a novel temporal coherence degree metric to evaluate the temporal coherence of the decolorized video. Compared with current methods, the proposed approach shows all around better performance in time efficiency, temporal coherence, and quality preservation.

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Temporal Coherent Video Decolorization Using Proximity Optimization

Cited by 4 publications

References 8 publications

Two Decades of Colorization and Decolorization for Images and Videos

Two Decades of Colorization and Decolorization for Images and Videos

Decolorization

Video Decolorization Using Visual Proximity Coherence Optimization

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